---
license: apache-2.0
base_model: bert-base-multilingual-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: bert_product_classifier_final
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# bert_product_classifier_final

This model is a fine-tuned version of [bert-base-multilingual-uncased](https://huggingface.co/bert-base-multilingual-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2344
- Accuracy: 0.9470
- F1: 0.9466
- Precision: 0.9467
- Recall: 0.9470

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.85          | 1.0   | 960  | 0.2943          | 0.9090   | 0.9074 | 0.9091    | 0.9090 |
| 0.2538        | 2.0   | 1920 | 0.2250          | 0.9332   | 0.9331 | 0.9331    | 0.9332 |
| 0.1468        | 3.0   | 2880 | 0.2372          | 0.9384   | 0.9388 | 0.9396    | 0.9384 |
| 0.0937        | 4.0   | 3840 | 0.2344          | 0.9470   | 0.9466 | 0.9467    | 0.9470 |


### Framework versions

- Transformers 4.32.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3